My name is Lisa Walter. I'm a biotech analyst here at RBC Capital Markets, and today is my great privilege to host Wave Life Sciences for a fireside chat as part of our 2024 Global Healthcare Conference. Representing the company today, we have Paul Bolno, who's the President and CEO of Wave. Paul, thanks so much for being here today. How are you doing?
Well, thank you. Thank you, Lisa, too, for having us.
Of course. So I always like to start off with some big picture questions. Can you remind us what are the latest developments with Wave, and maybe what are some of the key upcoming catalysts for 2024?
Yeah, I think as we come into 2024, it's going to be a very important year for Wave on a number of levels. So we have what I would call four key clinical catalysts. So the first will be the first data ever on RNA editing. And I think that's incredibly important with the Alpha-1 antitrypsin program, as it'll be the first time that we see data on proof of mechanism with a GalNAc-conjugated AIMer, in this case an editing oligonucleotide, to look at the ability to translate preclinical data into clinical data, meaning can we see the production of corrected M protein? Can we measure that, and really test the thesis of GalNAc translation from the mouse model, our non-human primate data, into humans?
Secondly, we'll have our update on potential as early as the end of this year, going into first quarter of 2025, the inhibin GalNAc-conjugated siRNA program for obesity transitioning. And then in Q3, we'll have our DMD data on dystrophin for N531 for exon 53 amenable boys. And ultimately, before that, we'll have in Q2 the data on WVE-003, the first allele-specific silencing therapy for Huntington's disease. So across this year in Q2, Q3, across 2024, and then the transition to obesity, I think it's going to be an important year across multiple modalities as we transition to data and ultimately the next steps for these programs.
Got it, got it. Maybe we should just touch on the platform for a second. I think most investors think of Wave as specifically an antisense oligonucleotide company. But recently, Wave has really expanded the platform technology to include RNAi and RNA editing as well. So can you just remind investors about the full suite of oligo technology that Wave has in-house?
Yeah, and it's a wonderful question because I know we all tend to put things into boxes because it makes it a lot easier to describe it.
For example , yes.
Yeah, it's, you know, you're an antisense company, you're an RNAi company, you're an exon-skipping company. And I think when we really stepped back to the formation of Wave now well over a decade ago, and this is important as we think about opportunity sets within each one of these technologies, we get a lot of questions of why are we seeing editing that's very distinct and different than our peers, hence being able to use GalNAc and see robust editing. I think it really comes down to chemistry. And it's hard at its core, Wave has for the last 10 years been a chemistry, an oligonucleotide chemistry company that, in our mind, really is focused on creating best-in-class oligonucleotide guide strands.
If we think about the opportunity in front of us, if you create an optimized chemistry around an oligonucleotide, then actually the repertoire inside the cell, the enzymes that are inside our cells that are responsible for editing, for silencing, for splicing, we can harness those internal enzymes, continue to identify additional opportunities, and really provide that best-in-class chemistry to unlock that opportunity. Once we've unlocked the opportunity of a specific enzyme, then we can really expand that into a target universe. And so the discipline around each one of these clinical catalysts are, to your point, they each open up an opportunity set. Antisense opens up an opportunity in CNS and allele-specific silencing as it relates to Huntington's disease. If these data are positive and supportive, it means we can expand that universe.
DMD gives us the ability to access muscle and look at exon-skipping and splice correction, opens up an opportunity around that area. Our AIMers, and really where directionally we've been making substantial investments, are around our AIMer technology, utilizing GalNAc initially, but see substantial editing without GalNAc in other tissues. Again, on Alpha-1 antitrypsin, that data doesn't just advance Alpha-1 antitrypsin. It opens up the universe of RNA editing capabilities. And as you said, at the end, transitioning into the clinic, as we round out the year, GalNAc-conjugated siRNA, whereas we published last year, we see more potent and durable silencing than the best-in-class commercial products within siRNA, really opening up that field for both hepatic editing and, as we've shared, extra hepatic, sorry, silencing and extra hepatic silencing as well.
Got it. Very helpful. So you mentioned one of the catalysts that you're really interested in is the RNA editing clinical update that's supposed to come later this year. So maybe let's talk about the A1AT program first. So this is, you know, the first RNA editing program that is in the clinic. Can you remind us why A1AT is such a good indication for RNA editing?
I think it's an important one because it's accessible. So we know that the disease driver - and we always start with biology - so it's not just a matter of, you know, here's a tool, let's kind of force it to do a job. It's what's the right job for the right tool? We have a variety of genetic opportunities in front of us. And so A1AT gave us an opportunity to say, in Alpha-1 antitrypsin deficiency, for those who are unfamiliar, you have both liver complications. And this is specifically talking about the ZZ patients, so about 100,000 patients in the U.S. and another 100,000 in Europe. These are patients who have no M protein, so they're homozygous null. And what they end up doing over the continuum is they have hepatic complications and pulmonary complications. The current treatment opportunities and really the commercial treatment opportunities available today is all about pulmonary.
It's IV protein replacement therapy. The emerging technologies on the siRNA front are all about turning off the spigot. If you can turn off the spigot, prevent misfolded protein from aggregating in the liver, you fix the liver. The continuum of these ZZ patients, if they progress, they typically present with respiratory complications. They get seen, they get evaluated to rule out, you know, for COPD and complications. They get identified as being an Alpha-1 antitrypsin patient, and then they go on to have a hepatic evaluation and oftentimes can have hepatic manifestations. So the thought in treating the disease was ultimately, if you could correct the mutation that causes the misfolded protein, you could end up creating normal functional wild-type protein that could protect the lung. But also by making that correction, you reduce the formation of liver aggregates, so you fix the liver.
So an ideal therapy, one, in its manifestation of the disease is a mutation that could be corrected, but also in terms of ultimately the treatment paradigm shift for the population. So we use the model. The benefit of the SERPINA1 model is it's translated, creates a misfolded protein. If you wait to that model has the disease, that model has liver aggregates, liver complications. And so it's a great model for studying the ability to repair the protein and look at what the opportunity is once you treat that protein. So we ran the model. We showed by looking at that translation that when the model becomes a SERPINA1 essentially patient, so it drops well below 11 micromolar, we could treat that model, we could generate the healthy protein, and we could see that that manifestation, we created protein at the level of normal patients.
And I should step back and say, to your point of why this is an important disease, is it is one that the heterozygous patients, these MZ patients, present with normal phenotypes. So they have more normal lung function and liver function. So really, it lends itself to the ability that if you get 50% editing, if you could correct a ZZ patient to an MZ patient, you could restore normal physiology. And so you could recapitulate that in the SERPINA1 model. We did that in terms of protein level, as I said, you know, restoring protein to levels of normal patients who at their native are about 20 micromolar.
Importantly, and I think this is the benefit of the therapies, you could really test whether or not not only can you create more protein, but we were able then, because these mice do have aggregates, when you let them establish the disease, we could go back and look at the ability to clear hepatic aggregates. So it is important that our program, and I think we need to, while it's a disease that when we announced we were going into it, a number of subsequent companies have said, you know, to your point on AATD being an interesting opportunity in editing, we've seen a lot of new entrants come in around AATD. And I think the important piece is to not think about it as lung versus liver, but really how are you ultimately changing that treatment paradigm?
So being able to show substantial protein in that we're correcting the protein to levels that are now achieving normal levels in the SERPINA1 model, being able to clear hepatic aggregates, and actually showing that you could restore normal liver hepatocyte health also speaks to the ability to translate the disease. The benefit ultimately, and why I think it's an attractive indication for us to pursue for treating patients, but also for testing and unlocking the value across the editing portfolio, is we are able to assess those same biomarkers in patients, meaning looking for the presence not just of increase in total protein, but corrected M protein. ZZ patients have no M protein. So any M protein that patients are producing is because we've underlying corrected the mutation. So it gives us an opportunity to cross-reference our animal data to ultimately human data.
Got it, got it. So we know Wave recently had the CTA cleared to initiate the RestorAATion-2 study, which is essentially a dose-finding study to enroll A1AT patients specifically. However, the RestorAATion-1 study has already been ongoing with normal healthy volunteers for about the last six months or so. So just wondering, what learnings have you gotten from the normal healthy volunteers that kind of have helped you to inform the design of RestorAATion-2 with patients?
So at the beginning, and it's been great to have a—I always say it was nice that we could go into normal healthy volunteers. So I think it corroborated what we've been saying for a long time, which is that RNA editing is different than DNA editing. And by using RNA editing, it's very analogous to what one can do with other RNA oligonucleotide modalities, RNAi, etc. So the benefit for us always in the healthy volunteer study was to expedite dose range finding, to get to RestorAATion-2 and start RestorAATion-2 at a dose that we would anticipate engaging target. And we can establish that. And I think this is, again, a big differentiator between our program and all of the other emerging AATD programs in preclinical development are really the ability to use GalNAc. And I think GalNAc-conjugated oligonucleotides are important because of two key features.
One, you know, you can look at predictive pharmacology, meaning we can look at how you move from mouse to non-human primates to humans. And you can establish that paradigm going forward because you've got an active mediated receptor that's on cells, and then you're looking at surface area predictions as you go forward. So that lets us think about calculating what the dose would be from a mouse to a non-human primate to human. Just for the sake of giving you concept, the dose that we were using in that animal study, the SERPINA1 study, is a human equivalent dose of about 0.75 mg/kg - 1 mg/kg. So we're able to kind of think and look at predictive of and ultimately establish what that dose threshold would be in humans.
I think the second piece, which is to come after we achieve potential proof of mechanism, is going to be the second feature that's a benefit of GalNAc is the ability to then replicate that data, not just on that program, but now having a better predictive analysis of how AIMers will translate from liver to humans across the other five GalNAc-conjugated AIMer programs that are in development. So a lot better predictive pharmacology, moving away from LNPs. LNPs have their own challenges, not just as it relates to potential liver hepatotoxicity, but also into predictive pharmacology. So for us, bringing that GalNAc program forward really lets us establish that dose to establish that starting point, RestorAATion-2, that dose is expected to engage target. And then we have two other dose cohorts.
For RestorAATion-2, I think what's important to understand is it's not about doing dose escalation purely. It's about establishing, given that first dose is expected to engage target, both a dose and a dose frequency that ultimately becomes the defining characteristic of the program. And so that's how RestorAATion-2 is going to be used as more to do dose range finding and frequency.
Got it, got it. So as you mentioned, we're likely to get proof of concept data from A1AT patients sometime this year. But, you know, given the CTA has just cleared, we're already, you know, it's already May, we're already at the midpoint of the year. Should we only expect to see a handful of patients with the initial data release?
So I think our guidance on proof of mechanism is really we take patients who are disease null. So these are patients who produce no protein. And the ability to demonstrate that we can correct protein and that we can then have, again, guidance of the starting point. So if we think about our opportunity across multiple cohorts to establish ultimately a dose and dose frequency, I think these data are going to be important in establishing that foothold on separating now a preclinical data set with a human clinical data set that can predict where we're going. And I think, you know, we're excited to have that data. I think it will be defining for the AATD field and program. Equally importantly, as we've said before, it's going to be important in defining how we move our other AIMers forward after establishing that proof of mechanism.
Got it. And what level of normal A1AT in the serum would you consider a success in sort of the proof of concept stage?
Yeah, so there's movement of, and this is important when we think about proof of mechanism, is total A1AT will continue to follow. We know that there's discussions around, you know, is 11 micromolar enough? Do you need more? I think it is important to really reflect on, you know, how we came about with 11 micromolar. Because, you know, if you think about how protein replacement therapy came into being, people were like, we're going to replace protein. We need to establish a normal level. They looked at the MZ patients and said they have a normal pulmonary phenotype. They have a baseline level. The lowest level in an MZ patient is 11 micromolar. What they forgot was that in that patient population, they have both an M allele and a Z allele. So they have a normal allele that can produce protein.
So they were taking ZZ patients and using IV protein replacement to take them to that level. But those patients had no other functional reserve around the M allele. For editing, we're doing something completely different, right? We're taking patients who are ZZ patients and turning them into MZ patients. So it really is about recapitulating that phenotype. So 11 micromolar to higher is important. 20 is the lower bounds of a normal healthy individual. So I think we've achieved an excess of that in the preclinical models. We'll have opportunities to look at it. But total protein is not the measurement ultimately of success on proof of mechanism. The benefit that we have in ZZ patients in terms of being able to look and evaluate the program is that these patients have zero.
So a lot of times we're thinking about this in the context of some of the other what I call kind of Z protein disaggregators, right? The ones that are really pushing more protein out. We're actually correcting the protein. Therefore, ZZ patients have zero M protein. So not only looking at total protein, but most importantly in this data set, evaluating M protein in the serum. Any M protein in the serum is produced because you've edited and created that protein. So that level of M protein will be an important indicator as we look at the data set this year.
Got it. Very, very helpful. So the total protein, but also the level of normal protein that's expressed will be important to see.
The normal protein is critical. I mean, if you're editing, you're producing M protein, then you should be following the M protein levels. I think, you know, we should be holding DNA editing to the same category. We should all be looking at levels of normal M protein, not isoforms, but the actual protein itself.
Got it, got it. Well, I could spend all day on A1AT, but maybe we should move on to the obesity program and the inhibin target. So we actually hosted a KOL last Friday with an obesity specialist. And we did ask her about the inhibin target. And she was excited about it. However, she did mention one thing, that she had some concerns about actually reducing the visceral fat too much, because you do need some visceral fat in your body for normal daily function. So is there going to be a need to find a sweet spot in terms of reducing the fat to the point where you're at a normal healthy level, but avoiding reducing it, you know, too low where maybe some of your normal bodily functions don't perform as they're supposed to? What are your thoughts on that?
So I think if we step back and think about what we're all trying to do in the field of obesity, and obesity is a public health disease, and we're learning that as we watch the experience with GLP-1s, is I think rapid weight loss down to zero fat. I mean, if we use that as a metric, it's not a good thing, right? I mean, I think we can all universally agree that you're right. There is a normal balance of and body composition. The benefit that we have with inhibin E is human examples of it. So I think the advantage that we've all seen, the reason we came into the field of obesity wasn't just because we said, wow, GLP-1s are interesting. Obesity is a space to go into. Let's do that.
The principles that we've used to build targets are the same as we approached obesity, as we approached Alpha-1 antitrypsin deficiency. We've got a genetic root cause of the disease. In this case, the UK Biobank data, really looking at a protective loss of function variant where you see in heterozygous patients a reduced level, 50% of inhibin E, and you see an improvement in outcomes in terms of visceral fat, in terms of reduced triglycerides and LDL, cardiovascular outcome benefits, type 2 diabetes outcome benefits, and reduced waist-to-hip ratio. So if we think about the driver in this target of genetics, it's absolutely, you know, validated based on human experience. I think if we think about what we've seen in the animal model, we see weight loss similar to semaglutide as we shared in our last earnings.
So I think, you know, where we are within a battle of weight is not shifting the scale to a zero visceral fat. I think what we're seeing is normal apportioning of fat, weight loss that looks to be corrected, and recapitulating what's seen in normal patients. I think that's exciting for the field because that weight loss we saw doesn't come at the expense of muscle. So we were able to say no muscle loss. I think what's also exciting about the program in the most recent data update we gave last week is the ability to stem rebound weight gain from sema. So I think the ability to really think about this class as being distinct and different from GLPs, and really about driving a genetically driven weight loss that's purely focused on the hepatocyte to adipocyte interaction, I think is really unique for the program.
I think as we think about the human experience, we can lean on, again, human data for what a loss of function can do.
Got it, got it. Well, maybe we should just touch on a couple of the clinical catalysts that are upcoming for DMD and the Huntington's disease program. So maybe on DMD, this is an antisense oligonucleotide and exon skipper for exon 53. And you have a potentially registrational trial ongoing, FORWARD-53, and that's expected to read out in the third quarter. What should we expect to see here for the topline data readout?
I think this is going to be an important translation of our early six-week data. So at the six-week time point, so that's after three doses, we saw the highest level of muscle concentration that's been seen with an oligonucleotide in splicing to date. So we saw 42,000 nanograms per gram. To put that into context, even with some of the conjugate programs, the data that's posted there is about 650 nanograms per gram. So if we think about exposure, we have exposure into muscle. If we think about the translation of is that productive, we saw 53% skip transcript. That's the most amount of exon skipping that's been seen across exons, so not just in exon 53, and even with conjugate programs. So we saw that translation. Early time point for protein production.
So the key driver in this next data set will be, at the six-month time point, the dystrophin level. So that'll let us continue to look at the accumulation of drug in the muscle, which, as we saw with the 25-day half-life at six weeks, we think this will be a monthly therapy. Being able to correlate that to greater than 5% protein production will be important as we think about a commercial path forward for exon 53. And then importantly, the other exons that utilize this chemistry that we have across the other exons amenable to skipping. So this will do two things. It'll obviously be an important key step on a path to potential registration for exon 53. It also unlocks, as part of what we would look forward to, which is an umbrella study for the other exons across that skipping amenable oligonucleotides.
Got it. So just wondering, what should we consider the bar for success here in terms of dystrophin expression? Obviously, VYONDYS 53 is already approved here, and Sarepta was able to show 0.92% of normal increase in dystrophin from baseline. So is that the goal? Is that the bar to beat?
No. I think we are very set that to have, in our minds, a viable path forward for this program in DMD. We want to see an excess of 5% dystrophin protein. You know, that, we believe, coupled with the potential for monthly dosing, which we know is different than that point. I was at weekly dosing. So doing that, and that was at 48 weeks. So seeing at six months, greater than 5% with a monthly administration, and a profile that looks very analogous from a safety standpoint to the standard of care, we think opens up the opportunity to drive switching not just for our 53 program, but importantly, as we look forward to the enrollment of other exons and expanding the aperture for treatment of DMD, we see that as an important stepping stone to really differentiate this program from the others in the class.
Got it, got it. Well, let's talk about the HD program quickly here. This is another antisense oligonucleotide program. We're expecting an upcoming, you know, clinical readout this quarter. This is a wild-type sparing approach that aims to selectively knock down the mutant huntingtin protein. Can you just briefly remind us why sparing a wild-type is so important for Huntington's disease?
Yeah, if we think about Huntington's disease, it's really having two components to it. It's a toxic gain of function that kills neurons, so a bad protein. And that's been demonstrated in a number of publications. You can predict when patients are going to progress based on their CAG repeat lengths. There's a very interesting paper out of UCL and University of British Columbia that showed that regardless of where people started with a mutant huntingtin level, when they transitioned from being asymptomatic to symptomatic, they all had a stepwise increase in their mutant huntingtin production. So mutant huntingtin kills neurons bad. If we look at the other side, I think the emergence of really understanding and digging into wild-type protein has really expanded over the last several years.
I think the work is, people used to think of it as this normal structural protein that's everywhere, and forget that it's a structural protein that interacts with other proteins and drives vesicle trafficking. There's ways to look at BDNF trafficking. And so it's a key driver in brain homeostasis. So it also functions outside of the CNS as well. There was a paper recently by Jeff Carroll looking back at a bunch of data and basically rerunning prospectively a mouse wild type knockout, and there were brain calcifications in the thalamic nucleus. Mice did worse. So there is data to suggest wild type sparing is important for neuronal health. The key driver for this data set is we've already shown single dose, we saw a 35% knockdown versus placebo and wild type sparing. So we know on the single dose, we could achieve that wild type sparing.
This will be the multi-dose data and a real opportunity to look with successive treatments, whether or not we see a 30% or greater knockdown in the mutant protein, sustained wild-type sparing. And I think the other key important metrics that we'll be looking at is avoiding some of the changes that have been seen with pan-silencing approaches in CNS imaging. So that is ventricular enlargement, hypertrophy, and hydrocephalus that have been seen with the small molecules like branaplam. They've been seen with the oligonucleotides like tominersen. So we'll be able to distinguish in this data set with extended follow-up, not just the target engagement and allele specificity, but also avoiding those changes within the brain structure.
Well, I think that's time, Paul. Thank you so much for joining us today, and appreciate you running through all the programs and the catalysts. What's going on for Wave in 2024?
It's a big year. Thank you, Lisa. We appreciate it.
Thank you.